Title :
Neural networks based parallel Viterbi decoder by hybrid design
Author :
Dong, Lin ; Wentao, Song ; Xingzhao, Liu ; Hanwen, Luo ; Youyun, Xu ; Wenjun, Zhang
Author_Institution :
Dept. of Electron. Eng., Shanghai Jiaotong Univ., China
Abstract :
A hybrid scheme integrating analog and digital methods is presented to design a Viterbi decoder based on neural networks. Due to its fully parallel architecture, neural networks based Viterbi decoder is significantly faster than the purely digital decoder. The fully parallel structure is obtained by implementing the branch metric calculation and add-compare-select (ACS) using the neural networks while the register exchange using parallel digital circuits. The hybrid Viterbi decoder is more suitable for VLSI implementation.
Keywords :
VLSI; Viterbi decoding; digital circuits; hybrid integrated circuits; integrated circuit design; maximum likelihood estimation; neural nets; parallel architectures; VLSI; add-compare-select; analog integrating method; branch metric calculation; digital decoder; digital integrating method; hybrid Viterbi decoder; hybrid design; maximum likelihood estimation; neural networks; parallel Viterbi decoder; parallel architecture; parallel digital circuits; parallel structure; register exchange; Convolution; Convolutional codes; Costs; Digital circuits; Maximum likelihood decoding; Neural networks; Parallel architectures; Registers; Very large scale integration; Viterbi algorithm;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1341914
